The invention relates to a method and apparatus for decoding a bit sequence from QPSK or QAM symbols
There are generally two known fundamental techniques for decoding QPSK or QAM symbols-hard demapping and soft demapping. In the hard demapping approach, the individual received QPSK or QAM signals (received vectors) are assigned based on an unambiguous decision to a constellation point (symbol vector) (see FIG. 16). With soft demapping, decoding of the received signals as data is performed, from which data and the reliability of a given decision for a specific QPSK or QAM symbol is obtained (see FIG. 17). Examples of these soft-decision-output demappers are found in U.S. Pat. Nos. 6,661,282; 6,115,435; 6,226,333 and 6,424,685 as well as the article by Tosato F., Bisoglia P. “Simplified Soft-Output-Demapper for Binary Interleaved. COFDM with Application to HIPERLAN/2”, Research Report, Department of Electronics, University of Padova, 2001.
This soft decision decoding, which weights the demodulated data by the error probability of the data, results in an improved forward error correction. For communication systems that utilize M-level QAM, the receiver thus requires a decoding algorithm that uses a two-dimensional (complex) receive signal to calculate the corresponding soft decision values as the input signals for the channel decoder. The prerequisite to ensure the reliability of this type of system is that the correct occurrence probability parameters for a given symbol are used as the basis for calculating the corresponding soft decision values.
As a rule, the receiver operates according to the maximum likelihood principle in which the individual probabilities are each multiplied and the receive sequence with the highest overall probability is selected. The main approach to determining the required individual probabilities is to use the Euclidean distance between receive vector and the nearest ideal symbol vector. In addition, it is generally assumed that the transfer channel shows a Gaussian amplitude distribution for the noise. Given a high signal-to-noise ratio, the logarithmic maximum likelihood function for this transfer channel is assumed to be approximately represented by:LLR˜(CTF(i)2/σ2*(min[r(i)−α0]−min[r(i)−α1]2)where:    i is an index for the carrier I,    CTF is a noise amplitude of the channel transfer function,    σ2 is a noise variance in the transfer channel,    r(i) is a receive vector with the coordinates I/Q,    α0 is the set of constellation points that correspond to a transmitted “0” (corresponding to the “ideal” symbol vectors for a transmitted “0”), and    α1 is the set of constellation points that correspond to a transmitted “1” (corresponding to the “ideal” symbol vectors for a transmitted “1”).
In coded orthogonal frequency division multiplexing (COFDM) systems, the soft information for the forward error correction (FEC) should for this reason be computed from the energy of the given carrier, the detected noise energy, and the probability of the corresponding constellation point.
The prior-art approach to accomplishing this starts with a fixed noise energy.
Calculation of the soft information is frequently implemented using mapping or lookup tables, see U.S. Pat. No. 6,115,435. Using this approach, the handling of the various constellations or hierarchy modes, such as those supporting, for example, DVB-T (Digital Video Broadcasting—terrestrial), specifically, 16-QAM, 64-QAM, a non-hierarchical constellation, a hierarchical constellation, et cetera, is difficult.
If, on the other hand, the decoding characteristic is calculated explicitly, the implementation is often either too complex, or significant approximation errors occur. For example, although U.S. Pat. No. 6,424,685 provides a comparatively simple calculation of the decoding characteristic from polar coordinates, considerable effort is required to adapt to the different constellations or hierarchy modes.
To simplify the decoding process, recent publications propose a transformation of the received constellation vectors into a simpler constellation arrangement. The term used here is “remapping”. For example, U.S. Pat. No. 6,661,282 describes a remapping by subtraction of an offset. However, this procedure is suitable only for the 16-QAM method. However, U.S. Pat. No. 6,226,333 describes the decoding of QAM symbols from a single quadrant by employing a rotator.
Therefore, there is a need for a technique of decoding QPSK or QAM symbols in which different constellations and hierarchy modes are easily implementable. In addition, the technique should have a high degree of reliability in predicting the decoded QPSK or QAM symbols.